A Process to Support Analysts in Exploring and Selecting Content from Online Forums
作者机构：Department of InformaticsPontifical Catholic University of Rio de JaneiroRio de JaneiroBrazil Institute of Mathematical and Computer SciencesUniversity of Sao PauloSao CarlosBrazil
出 版 物：《Social Networking》 (社交网络（英文）)
年 卷 期：2014年第3卷第2期
页 面：86-93页
学科分类：1002[医学-临床医学] 100214[医学-肿瘤学] 10[医学]
基 金：sponsored by CNPq(Brazilian Council for Research and Development),process 142620/2009-2 FAPESP(State of Sao Paulo Research Foundation),process 2010/20564-8 and 2011/19850-9
主 题：Qualitative Analysis of Online Forums Explore and Select the Online Forums Content Machine Learning Hierarchical Clustering Terms Co-Occurrence Network Consolidated and Structured Results
摘 要：The public content increasingly available on the Internet, especially in online forums, enables researchers to study society in new ways. However, qualitative analysis of online forums is very time consuming and most content is not related to researchers’ interest. Consequently, analysts face the following problem: how to efficiently explore and select the content to be analyzed? This article introduces a new process to support analysts in solving this problem. This process is based on unsupervised machine learning techniques like hierarchical clustering and term co-occurrence network. A tool that helps to apply the proposed process was created to provide consolidated and structured results. This includes measurements and a content exploration interface.
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